Pretreatment Frequency of Circulating Th17 Cells and FeNO Levels Predicted the Real-World Response after 1 Year of Benralizumab Treatment in Patients with Severe Asthma

治疗前循环 Th17 细胞频率和 FeNO 水平可预测重度哮喘患者接受贝那利珠单抗治疗 1 年后的真实反应

阅读:12
作者:Yuuki Sandhu, Norihiro Harada, Hitoshi Sasano, Sonoko Harada, Shoko Ueda, Tomohito Takeshige, Yuki Tanabe, Ayako Ishimori, Kei Matsuno, Sumiko Abe, Tetsutaro Nagaoka, Jun Ito, Asako Chiba, Hisaya Akiba, Ryo Atsuta, Kenji Izuhara, Sachiko Miyake, Kazuhisa Takahashi

Abstract

Benralizumab treatment reduces exacerbations and improves symptom control and quality of life in patients with severe eosinophilic asthma. However, the determination of biomarkers that predict therapeutic effectiveness is required for precision medicine. Herein, we elucidated the dynamics of various parameters before and after treatment as well as patient characteristics predictive of clinical effectiveness after 1 year of benralizumab treatment in severe asthma in a real-world setting. Thirty-six patients with severe asthma were treated with benralizumab for 1 year. Lymphocyte subsets in peripheral blood samples were analyzed using flow cytometry. Treatment effectiveness was determined based on the ACT score, forced expiratory volume in 1 s (FEV1), and the number of exacerbations. Benralizumab provided symptomatic improvement in severe asthma. Benralizumab significantly decreased peripheral blood eosinophil and basophil counts and the frequencies of regulatory T cells (Tregs), and increased the frequencies of Th2 cells. To our knowledge, this is the first study to show benralizumab treatment increasing circulating Th2 cells and decreasing circulating Tregs. Finally, the ROC curve to discriminate patients who achieved clinical effectiveness of benralizumab treatment revealed that the frequency of circulating Th17 cells and FeNO levels might be used as parameters for predicting the real-world response of benralizumab treatment in patients with severe asthma.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。